Machine Learning-Based Prediction of Postoperative Deep Vein Thrombosis Following Tibial Fracture Surgery by Humam Baki, İsmail Bülent Özçelik

“…The top-performing model (random forest with RFE) attained an AUC of ~0.99, while several others (including LightGBM and SVM-based models) also reached AUC values in the 0.97–0.99 range. …”
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Artificial Intelligence-Based Prediction of Bloodstream Infections Using Standard Hematological and Biochemical Markers by Ferhat DEMİRCİ, Murat AKŞİT, Aylin DEMİRCİ

“…SHAP analysis revealed that age and PCT were the most influential features with both statistical and clinical relevance. Basophil count, while ranked highest by SHAP, showed low sensitivity, highlighting the difference between algorithmic weight and bedside utility. …”
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Identification of glucocorticoid-related genes in systemic lupus erythematosus using bioinformatics analysis and machine learning. by Yinghao Ren, Weiqiang Chen, Yuhao Lin, Zeyu Wang, Weiliang Wang

“…Among these, 1,458 genes were upregulated, while 1,223 were downregulated in cluster_1. GSVA showed significant changes in the pathways associated with cluster_1. …”
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Sensor‐Guided Smart Irrigation for Tomato Production: Comparing Low and Optimum Soil Moisture in Greenhouse Environments by Ibrahim Dirlik, Ferhat Uğurlar, Cengiz Kaya

“…Treatment 1 (T1) involved low moisture with significant fluctuations (55%–85% soil moisture), while Treatment 2 (T2) maintained optimal and stable moisture levels (70%–85%). …”
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Ensemble Transformer–Based Detection of Fake and AI–Generated News by Md. Ishraquzzaman, Mohammed Ashraful Islam Chowdhury, Shahreen Rahman, Riasat Khan

“…This work leverages advanced natural language processing, machine learning, and deep learning algorithms to effectively detect fake and AI–generated content. …”
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Prediction of hypertensive disorders in pregnant women in the «gray» risk zone following combined first-trimester screening by N. V. Mostova, V. V. Kovalev, E. V. Kudryavtseva

“…Group 1 consisted of female patients at high РЕ risk (1:100 and greater), while female patients at moderate risk (1:101–1:250) and low risk (below 1:250) were included into Group 2 and Group 3, respectively. …”
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Retrieval of top-of-atmosphere fluxes from combined EarthCARE lidar, imager, and broadband radiometer observations: the BMA-FLX product by A. Velázquez Blázquez, C. Domenech, E. Baudrez, N. Clerbaux, C. Salas Molar, N. Madenach

“…The radiance-to-flux conversion algorithms have been successfully validated through end-to-end verification using L1 and L2 synthetic data for three EarthCARE orbits. …”
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Streaming LiDAR Scene Flow Estimation by Mazen Abdelfattah, Z. Jane Wang, Rabab Ward

“…This achieves substantial speedups while maintaining, and in some cases surpassing, full-scan accuracy. …”
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The Philosophy of Semar as an Ethical Framework for the Use of Artificial Intelligence by Mohamad Khusnial Muhtar, Naufal Robbiqis Dwi

“…<div>Artificial intelligence (AI) is a multidimensional phenomenon that profoundly impacts various aspects of&nbsp;<span style="font-size: 1rem;">modern human life. While global discussions on AI ethics have predominantly centered on Western&nbsp;</span><span style="font-size: 1rem;">perspectives, this study explores ethical AI development through the lens of Semar philosophy,&nbsp;</span><span style="font-size: 1rem;">representing the local wisdom of Nusantara. …”
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Unmanned Aerial Surveillance and Tracking System in Forest Areas for Poachers and Wildlife by R. G. Sangeetha, Yash Srivastava, C. Hemanth, Harsh Sankar Naicker, Abhijith P. Kumar, Sreejith Vidhyadharan

“…Using a robust two-fold collision avoidance system, the drone travels autonomously while avoiding obstacles in the dense forest cover. …”
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Elucidating the role of LGALS3BP in coronary atherosclerosis: integrating bioinformatics and machine learning for advanced insights by Suzhen Zhao, Chuanxin Zhao, Linlin Wang, Baoe Cheng, Man Zheng, Xiuyun Wang

“…The relationship between LGALS3BP expression and immune processes was explored using CIBERSORT and ESTIMATE algorithms, which indicated a positive association between higher LGALS3BP expression and increased immune cell infiltration. …”
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Inertial measurement unit technology for gait detection: a comprehensive evaluation of gait traits in two Italian horse breeds by Vittoria Asti, Michela Ablondi, Arnaud Molle, Andrea Zanotti, Matteo Vasini, Alberto Sabbioni

“…A high variability was observed in the accuracy of the SVM model, ranging from 55 to 100% while the other two models showed higher consistency, with accuracy ranging from 74 to 100% for the GBM and from 64 to 88% for the KNN. …”
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Evaluation of Diagnostic Recommendations Embedded in Medication Alerts: Prospective Single-Arm Interventional Study by Yu-Chen Liu, Guan-Ling Lin, Jeremiah Scholl, Yi-Chun Hung, Yu-Jing Lin, Yu-Chuan Li, Hsuan-Chia Yang

“…The system provided diagnostic recommendations based on machine learning algorithms trained on data from the National Health Insurance Research Database. …”
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Optimizing role assignment for scaling innovations through AI in agricultural frameworks: An effective approach by Sonia Bisht, Ranjana, Swapnila Roy

“…The proposed approach serves as a blueprint for agricultural enterprises aiming to adopt AI technologies while ensuring optimal utilization of human and technological resources. …”
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Association between hemoglobin A1c variability and hypoglycemia-related hospitalizations in veterans with diabetes mellitus by Julia C Prentice, Molly J Y Zhao, David C Mohr, Paul R Conlin

“…HRH was identified during a 2-year follow-up period from Medicare and the Veterans Health Administration through validated algorithms of International Classification of Diseases (ICD)-9 and ICD-10 codes. …”
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Molecular insights into ulcerative colitis and orbital inflammation by Kang Tan, Pei Liu, Zixuan Wu, Xi Long, Yunfeng Yu, Pengfei Jiang, Qinghua Peng

“…Abstract Ulcerative colitis (UC) is an increasingly prevalent inflammatory condition affecting the intestinal mucosa, while nonspecific orbital inflammation (NSOI) is a common non-neoplastic orbital disorder. …”
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Research on Method for Intelligent Recognition of Deep-Sea Biological Images Based on PSVG-YOLOv8n by Dali Chen, Xianpeng Shi, Jichao Yang, Xiang Gao, Yugang Ren

“…In the neck network, a Slim-Neck module (GSconv + VoVGSCSP) is incorporated to reduce the parameter count and model size while simultaneously augmenting the detection performance. …”
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The Effect of Family-Centered Empowerment Model Based on Multimedia Education on the Quality of Life of Children Aged 8-12 Years with Thalassemia by Ayoub Mohamadian, Ali Moeini, Mahnaz Sanjari, Zahra Abdullahzade

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EMSAM: enhanced multi-scale segment anything model for leaf disease segmentation by Junlong Li, Quan Feng, Jianhua Zhang, Jianhua Zhang, Sen Yang

“…The LFEM utilizes multiple convolutional layers to capture lesion boundaries and detailed characteristics, while the GFEM fine-tunes ViT blocks using a Multi-Scale Adaptive Adapter (MAA) to obtain multi-scale global information. …”
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Learning Rate Tuner with Relative Adaptation (LRT-RA): Road to Sustainable Computing by Saptarshi Biswas, Sumagna Dey, Subhrapratim Nath

“…Previous solutions, such as learning rate scheduling (LRS) and adaptive learning rate (ALR) algorithms like RMSProp and Adam, added complexity by introducing new hyperparameters, thereby increasing the cost of model training through expensive cross-validation experiments. …”
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